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Record W4407653658 · doi:10.1002/ange.202422967

Direkte CO<sub>2</sub>‐Aktivierung und Umwandlung in Ethanol durch reaktive Sauerstoffspezies

2025· article· de· W4407653658 on OpenAlexaff
Alina Meindl, Daniel M. Heffernan, Jürgen Kudermann, Nicole Strittmatter, Mathias O. Senge

Bibliographic record

VenueAngewandte Chemie · 2025
Typearticle
Languagede
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsTrinity College
FundersSalzburger Landesregierung
KeywordsEthanolOxygenChemistryReactive oxygen speciesEnvironmental chemistryOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

Abstract Der wachsende Energiebedarf und die übermäßige Nutzung fossiler Brennstoffe stellen eine der größten Herausforderungen für die Menschheit dar. Die Speicherung von Solarenergie in Form von chemischen Bindungen zur Erzeugung von solaren Brennstoffen oder Chemikalien ohne zusätzliche Umweltbelastungen ist eine wichtige Voraussetzung für eine nachhaltige Zukunft. Hier nutzen wir die künstliche Photosynthese und stellen ein photokatalytisches System auf der Basis von dPCN‐224(H) MOF vor, das reaktive Sauerstoffspezies (ROS) zur Aktivierung und Umwandlung von CO2 in Ethanol unter atmosphärischen Bedingungen, bei Raumtemperatur und in 2–5 Stunden Reaktionszeit nutzt. Das System bietet eine CO2‐ zu‐Ethanol‐Umwandlungseffizienz (CTE) von 92 %. Darüber hinaus ermöglicht diese Methode auch die Umwandlung von CO2 durch direkte Luftabscheidung (DAC), was sie zu einer schnellen und vielseitigen Methode sowohl für gelöstes als auch für gasförmiges CO2 macht.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.277
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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